Abstract:
Gene expression signatures consisting of tens to hundreds of genes
have been found to be informative for different biological states.
Recently, many computational methods have been proposed for biological
interpretation of such signatures. However, there is a lack of methods
for identifying cell signaling pathways whose deregulation result in
an observed expression signature. We present a strategy for
identifying such signaling pathways and evaluate the strategy using
six human and mouse gene expression signatures.